The video traffic demands are increasing over a mobile network through wireless link cannot corporate with the demand of video traffics. The increasing traffic demand is accounted by video streaming and downloading. Hence, there is a gap between link capacity and traffic demands along with the time varying condition which is result in the poor quality of video streaming service over a mobile network such as sending long buffering time and intermittent disruptions due to limited bandwidth and link condition. By leveraging cloud computing technology, we propose a new mobile video streaming framework which has two main parts : Efficient social video sharing and Adaptive mobile video streaming which built a private agent which provides video streaming service for each mobile user in the network efficiently. To demonstrate its performance we implement a prototype of AMES-Cloud framework. Thus, it is crucial to improve the video quality service of streaming while using the computing resource and networking efficiently and also provides preservation over cloud computing
%0 Journal Article
%1 Krishnarao_2015
%A Hedau, Miss. Payal Krishnarao
%A Chaudhari, Prof. Manoj S.
%D 2015
%I Auricle Technologies, Pvt., Ltd.
%J International Journal on Recent and Innovation Trends in Computing and Communication
%K (SVC ) Adaptive Cloud Efficient Mobile Scalable Traffic coding computing demand networks sharing streaming video
%N 1
%P 18--21
%R 10.17762/ijritcc2321-8169.150105
%T Review on AMES-Cloud Using Preservation, Fetching and Decisive Video Streaming Over Cloud Computing
%U http://dx.doi.org/10.17762/ijritcc2321-8169.150105
%V 3
%X The video traffic demands are increasing over a mobile network through wireless link cannot corporate with the demand of video traffics. The increasing traffic demand is accounted by video streaming and downloading. Hence, there is a gap between link capacity and traffic demands along with the time varying condition which is result in the poor quality of video streaming service over a mobile network such as sending long buffering time and intermittent disruptions due to limited bandwidth and link condition. By leveraging cloud computing technology, we propose a new mobile video streaming framework which has two main parts : Efficient social video sharing and Adaptive mobile video streaming which built a private agent which provides video streaming service for each mobile user in the network efficiently. To demonstrate its performance we implement a prototype of AMES-Cloud framework. Thus, it is crucial to improve the video quality service of streaming while using the computing resource and networking efficiently and also provides preservation over cloud computing
@article{Krishnarao_2015,
abstract = {The video traffic demands are increasing over a mobile network through wireless link cannot corporate with the demand of video traffics. The increasing traffic demand is accounted by video streaming and downloading. Hence, there is a gap between link capacity and traffic demands along with the time varying condition which is result in the poor quality of video streaming service over a mobile network such as sending long buffering time and intermittent disruptions due to limited bandwidth and link condition. By leveraging cloud computing technology, we propose a new mobile video streaming framework which has two main parts : Efficient social video sharing and Adaptive mobile video streaming which built a private agent which provides video streaming service for each mobile user in the network efficiently. To demonstrate its performance we implement a prototype of AMES-Cloud framework. Thus, it is crucial to improve the video quality service of streaming while using the computing resource and networking efficiently and also provides preservation over cloud computing},
added-at = {2015-08-03T07:24:10.000+0200},
author = {Hedau, Miss. Payal Krishnarao and Chaudhari, Prof. Manoj S.},
biburl = {https://www.bibsonomy.org/bibtex/28528eb5996ce0bef34842b73256e13d6/ijritcc},
doi = {10.17762/ijritcc2321-8169.150105},
interhash = {dca7e10eba5e59e05e673c20bee13ad8},
intrahash = {8528eb5996ce0bef34842b73256e13d6},
journal = {International Journal on Recent and Innovation Trends in Computing and Communication},
keywords = {(SVC ) Adaptive Cloud Efficient Mobile Scalable Traffic coding computing demand networks sharing streaming video},
month = {january},
number = 1,
pages = {18--21},
publisher = {Auricle Technologies, Pvt., Ltd.},
timestamp = {2015-08-03T07:24:10.000+0200},
title = {Review on {AMES}-Cloud Using Preservation, Fetching and Decisive Video Streaming Over Cloud Computing},
url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150105},
volume = 3,
year = 2015
}